Exploring EEG Features for Differentiating Between Secure and Insecure Attachment Styles

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Attachment theory is a psychological framework that explains the nature and development of human attachment relationships. Studies have also found that our attachment style is prominent in how we form and behave in significant romantic relationships in our adult lives. Today, the current practice of measuring one’s attachment is either via psychotherapy-based treatment or self-report attachment questionnaires. However, self-report measures rely on an individual's self-awareness and willingness to accurately report their thoughts and feelings, which can be influenced by social desirability bias or other factors. Today, with the availability of various EEG-based features that show some differences in activation patterns, we explore whether the attachment styles can be differentiated, via brain waves activations, when participants played a simple unrelated task, the flanker task. Our results show that successful classification can be attained using frequency, temporal, or complexity-based features. These results provide a first example of the ability to classify the primary attachment based on EEG features instead of self-report questionnaires.

Original languageEnglish
Title of host publicationIntelligent Systems and Applications - Proceedings of the 2023 Intelligent Systems Conference IntelliSys Volume 4
EditorsKohei Arai
PublisherSpringer Science and Business Media Deutschland GmbH
Pages436-448
Number of pages13
ISBN (Print)9783031477171
DOIs
StatePublished - 2024
EventIntelligent Systems Conference, IntelliSys 2023 - Amsterdam, Netherlands
Duration: 7 Sep 20238 Sep 2023

Publication series

NameLecture Notes in Networks and Systems
Volume825
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

ConferenceIntelligent Systems Conference, IntelliSys 2023
Country/TerritoryNetherlands
CityAmsterdam
Period7/09/238/09/23

Keywords

  • Attachment theory
  • EEG
  • Lempel-Ziv complexity
  • Theta to Beta Ratio (TBR)

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